Sample Size Calculation: How Many Survey Responses Do You Need?

7 min read

Updated 2026-02-01

Guide

Determining the right sample size is crucial for survey research. Too small, and your results may not be statistically meaningful. Too large, and you waste resources.

Key Takeaways

•Sample size depends on confidence level, margin of error, and population variability
•For most surveys, 300-400 responses provide ±5% margin of error at 95% confidence
•Larger samples are needed for subgroup analysis
•Response rates affect how many invitations you need to send
•Population size matters less than you think once you exceed a few hundred

Factors Affecting Sample Size

Confidence Level: How sure you want to be (95% is standard).

Margin of Error: The range within which true value likely falls (±5% is common).

Population Variability: How diverse opinions are (assume 50% when unknown).

Sample Size Formula

n = (Z² × p × (1-p)) / E² where Z = z-score for confidence level, p = expected proportion, E = margin of error.

For 95% confidence with ±5% margin: n = (1.96² × 0.5 × 0.5) / 0.05² = 384

Quick Reference Table

At 95% confidence: ±10% needs 96 responses, ±5% needs 385, ±3% needs 1,067, ±1% needs 9,604.

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Frequently Asked Questions

For general surveys with ±5% margin at 95% confidence, 385 responses is standard. For quick insights, 100-200 may suffice.

Minimally, once the population exceeds a few thousand. Sampling 400 from 100,000 vs 100 million provides nearly identical precision.

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